Abstract: Disclosed is a computer-implemented method and system for estimating protein concentrations. The method comprises first generating a synthetic dataset based at least on protein signature or fingerprint data. Then, the method comprises training a model using in part the synthetic dataset, without requiring protein-specific calibration or training. Finally, the method comprises using the model to estimate or predict a percentage amount of a specific protein of interest (POI) in one or more heterogeneous samples, even if the POI was not used in modeling at the time of training.

Abstract: Provided herein are methods for precision fermentation that iteratively build models, collect data broadly, and deliver information to users both directly (via API or user interface) or through third party software. Furthermore, in addition to traditional facades and coordinated operations like sagas, subsystems often require the ad-hoc ability to communicate with each other like to operate on data about the same sample or strain across multiple services.

Abstract: Systems, methods, and computer-readable media are provided for determining treatments to apply to plants within control volumes having controlled agricultural environments. Each treatment comprises application of a set of setpoints, choosing a reproduction operation for the treatment, and selecting one or more previous sets from setpoints from one or more previously applied treatments, for use with the chosen reproduction operation.

Abstract: Systems, methods and computer-readable media are provided for determining optimum placement, within a grow space, of plants of different varieties. Sets of reference environmental setpoints each correspond to a desired predicted performance of a respective plant variety. Environmental condition metrics at different positions within the grow space are determined. An allocation of the plants is determined among different volumetric regions within the grow space based on predicted performance of the plant varieties as a function of position within the grow space.

Abstract: The present disclosure provides compositions for preparation of egg-like products.

Abstract: Systems, methods and computer-readable media are provided for determining optimum placement, within a grow space, of plants of different varieties. Sets of reference environmental setpoints each correspond to a desired predicted performance of a respective plant variety. Environmental condition metrics at different positions within the grow space are determined. An allocation of the plants is determined among different volumetric regions within the grow space based on predicted performance of the plant varieties as a function of position within the grow space.

Abstract: Systems, methods, and computer-readable media are provided for determining treatments to apply to plants within control volumes having controlled agricultural environments. Each treatment comprises application of a set of setpoints, choosing a reproduction operation for the treatment, and selecting one or more previous sets from setpoints from one or more previously applied treatments, for use with the chosen reproduction operation.

Abstract: Systems, methods and computer-readable media are provided for determining optimum placement, within a grow space, of plants of different varieties. Sets of reference environmental setpoints each correspond to a desired predicted performance of a respective plant variety. Environmental condition metrics at different positions within the grow space are determined. An allocation of the plants is determined among different volumetric regions within the grow space based on predicted performance of the plant varieties as a function of position within the grow space.